The subject matter disclosed herein relates generally to spectroscopy, and more particularly, to absorption spectroscopy for detection of moisture in a process gas involving cross interference. Examples of process gases include, but are not limited to, natural gas, cracked gas out of a steam cracker, polyethylene feedstock, and hydrogen recycle gas.
Absorption spectroscopy based moisture analyzers exist for determining moisture concentration in a sample gas. However, determination of the concentration of moisture (i.e., water vapor), in a process gas may be complicated. For example, spectral interference between moisture and background gas (i.e., the process gas minus moisture) may be severe enough to pose a challenge to achieve desired sensitivity or accuracy in determining the concentration of moisture in the process gas.
Differential spectroscopy may be employed to reduce the spectral interference from background gas to determine the concentration of moisture in a process gas. One example of a process used in differential spectroscopy may include recording a spectrum of the background gas, which is essentially dried process gas, subtracting this spectrum from a spectrum of the process gas to yield a differential spectrum, and determining the moisture concentration based upon the differential spectrum. However, this process requires a gas purifier and other requisite accessories to remove moisture from the process gas to record the background spectrum, which may be costly. Additionally, this process requires a switch between the sample gas to be analyzed (i.e., the process gas) and the reference gas (i.e., gas dried by the purifier, which is representative of the background gas), which may slow the system response time.
Moreover, there is no guarantee that the spectral interference would be effectively removed because the spectra of the sample gas and the background gas are not recorded at the same time and/or the chemical composition of background gas may vary over time, and, thus, its spectrum may vary over time.
Further, a process gas can vary in temperature, pressure, and composition. These variations may cause a calibration drift in tunable diode laser absorption spectroscopy (TDLAS) based moisture analysis, because the gas sample used for calibration of the equipment may not account for these variations. Accordingly, an approach that adequately addresses present issues regarding detecting moisture in a process gas is desirable.